Adults with Down syndrome show quantitative sleep electroencephalogram patterns similar to those observed in patients with Alzheimer’s disease
Sandra Giménez, Susana Clos, Leidy Y. Serna, Maria Carmona‐Iragui, Bessy Benejam, Monica Rojas, Alexandre Bejanin, Javier Arranz, Laura Videla, Isabel Barroeta, Mateus Rozalem Aranha, Alejandra O. Morcillo‐Nieto, Sara E. Zsadanyi, Miguel Angel Mañanas, Alberto Lleo, Sergio Romero, Juan Fortea- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
Down syndrome (DS) is a genetic form of Alzheimer’s disease (AD) with a preclinical AD biomarker changes similar to euploid forms of AD. In sporadic AD, sleep electroencephalogram (EEG) changes have been related to cognitive decline and AD progression. However, whether DS follows a similar pattern of sleep EEG changes has not been investigated. Here, we aimed to quantify sleep EEG pattern in adults DS using spectral analysis and entropy changes.
Method
Cross‐sectional study, 67 adults with DS (41.1±11.4 yo) without signs of AD cognitive decline, and 24 euploid adults (58.3±12.4 yo) performed a polysomnography with extended 19 channels EEG setup. For data analysis, EEG was segmented into 5s epochs and preprocessed by an automatic artifact rejection procedure based on amplitude and kurtosis. Power spectra at the common EEG bands were calculated separately for wake, for NREMS: N1, N2, N3 stages, N2 stage, slow wave sleep (SWS:N3 stage) and REM stage. Sample entropy was also calculated for each epoch. Differences in EEG power across sleep stages between groups were calculated and represented by statistical percentage differences in one channel (Fz‐derivation) and by statistical topographic maps in all 19 EEG channels. For the dynamic of the EEG spectrum, the average of delta and entropy activity was calculated in Fz for each NREM cycle, and for sigma activity in NREM‐REM cycles.
Result
As compared to the control group, subjects with DS presented overall and significant increments in the delta and theta band for all sleep stages, and across sleep cycles(p<0.01). Topographic maps showed also a generalized increase in the beta band (13‐35Hz) compared to controls, mainly for N2 and N3 stages. A general decrease in the sample entropy (p<0.01) was also observed for all the sleep stages, implying that Down subjects have more regular and deterministic EEG rhythms.
Conclusion
Subjects with DS present a high activity in the low frequency bands, detected in all EEG channels and all sleep and wake stages. These results follow the same tendency observed in the sleep EEG changes in preclinical AD, which evidence the suitability of adults with DS to study sleep EEG changes as possible AD biomarker.